Data mining is the process of automatically searching large volumes of data for patterns using tools such as classifiers. Data mining using a classifier involves sorting through large amounts of data and picking out relevant information. One technique known in the art is the use of logistic regression. Logistic regression is a mathematical technique that has never obtained full acceptance in the data mining community as a standard machine learning technique for large data sets. The reluctance to use logistic regression is largely due to the general belief that logistic regression is too computationally expensive and that it will not easily scale up to large data sets. Thus, some logistic regression techniques for classifier use are not well favored. A need exists to implement a classifier that uses logistic regression techniques and executes in a manner that is not prohibitive to realistic use.